Posts Tagged ‘income’

Several times a year, one money-minded organisation or another publishes a ‘rich list’. On this list are the names of the extraordinarily wealthy, the billionaires. Such a list is compiled by Forbes magazine. In this year’s list of billionaires, there are 90 Indians.

Perhaps it is the largest contingent of Indians on this list ever, perhaps their wealth is greater, singly and together, than ever before, perhaps the space below them (the almost-billionaires) is more crowded than ever. What must be of concern to us is the inequality that such a list represents. In the first two, perhaps three, Five Year Plans, cautions were expressed that the income (or wealth) multiple between the farmer and the labourer on the one hand and the entrepreneur or skilled manager on the other should not exceed 1 to 10.

In practice it was quite different, but the differences of the early 1990s – which is when economic liberalisation took hold in India – are microscopic compared to those of today. What’s more, the astronomically large differences in income/wealth of 2015 are actually celebrated as being evidence of India’s economic superpowerdom.

The current per capita national income is 88,533 rupees and it will take, as my disturbing panel of comparisons shows, the combined incomes of 677,713 such earners to equal the wealth of the 90th on the Forbes list of Indian billionaires. Likewise, there are six on the list of 90 with median incomes, and a median income is Rs 11.616 crore, which is equal to the entire Central Government budget outlay for agriculture (and allied activities) for 2015-16.

Close ranks of tall residential towers signal a new township on the outskirts of Beijing, P R China.

Some two years ago, it was calculated, the world firmly entered the urban age, for the available evidence pointed to a startling truth: more people now live in cities than outside them. The balance between urban and rural populations differs between countries, at times considerably. Chad and Congo have about the same number of people living in cities, 2.95 million and 2.96, but these urban populations are 22% of the total population for Chad and 65% of the total population for Congo.

Overall, the balance between urban and rural populations is thought, conventionally, to directly describe whether a country is likely to be in the high income or low income groups of countries. The Department of Economic and Social Affairs – a specialist agency of the United Nations – entrusts such calculations to its Population Division whose ‘World Urbanization Prospects’ found, in its 2014 revision, that the proportion of urban populations for high income countries was 80% while that for low income countries was 30%. This seems to lend weight to the conventional wisdom that it is cities that galvanise the creation of the sort of wealth which gross domestic product (GDP) growth depends on.

Cities are seen to harbour dynamism and vitality. For those who live in such cities, this is largely true. Residents of cities like Seoul (Korea), Lima (Peru), Bangalore, Chennai and Hyderabad (all India), Bogotá (Colombia), Nagoya (Japan), Johannesburg (South Africa), Bangkok (Thailand) and Chicago (USA) are very likely to agree that living and working in their respective cities has brought tham prosperity, and are less likely to ponder about this group of cities being the top ten in the world with populations under 10 million in 2014 (there are 28 cities worldwide with populations of at least 10 million).

There is however another aspect to the formation of cities. In 1927, the film Metropolis, conceived by Fritz Lang and delivered as an artfully stylised cinematic message, described the strains and dangers of the power that cities had already come to have over their residents. For Metropolis was a futuristic city where a cultured utopia existed above a bleak underworld populated by mistreated workers. Just over 50 years later, another film, Blade Runner (1982), blended science fiction with a disturbing portrait of a dystopian and dangerous cityscape that was both gigantic and technology-centric, through which the human element struggled to find meaning.

If Metropolis represented the post-industrial revolution European cityscape, then Blade Runner depicted the flagship of what has been called the Asian century, for its mesmerising and frightening urban backdrop was Tokyo then, and could well be China now. The Japanese capital remains in 2014 the world’s largest city with an agglomeration of 38 million inhabitants, followed by New Delhi with 25 million, Shanghai with 23 million, and Mexico City, Mumbai and São Paulo, each with around 21 million inhabitants. By 2030, so the projections say, the world will have 41 mega-cities of more than 10 million inhabitants.

For all their celebrated roles as centres of wealth, innovation and culture, these mega-cities and their smaller counterparts exert dreadful pressures on natural resources and the environment. These are already either unmanageable or uneconomical to deal with, more so in the rapidly growing urban centres of Asia and Africa. Despite the lengthening list of urban problems – most caused by rural folk flocking to cities faster than urban governance structures can cope with existing needs – demographers foresee that today’s trend will add 2.5 billion people to the world’s urban population by 2050. India, China and Nigeria are together expected to account for 37% of the projected growth of the world’s urban population between this year and 2050. It is there that the idea of the city, which so fascinated Fritz Lang, will be sorely tested.

While the principles are intended to provide practical guidance to governments, private and public investors, intergovernmental and regional organisations, civil society groups, research units and universities, donors and philanthropic foundations, they will be voluntary and will not be binding upon their signatories.

“The adoption of RAI will aid, in any host country, the tailoring of all policies and strategies to fit investors (foreign and domestic, for the technological advantages are now common, as much as the conduits of capital flow for food and agriculture investment are many) so that they can be ‘competitive’ in the market. Instead of prioritising a model of agricultural production where women, farmers/peasants, pastoralists and all small-scale food producers are at its core, in which agro-ecological forms of farming and raising livestock are supported, and through which local markets and economies are strengthened, the draft RAI principles will if accepted legitimise policies that put the government and country at the service of such investors (both foreign and domestic, it must be noted).”

Moreover, from the point of view of human rights terms this is discriminatory; and will turn a parlous situation into a destabilising one – already countries are falling short of their obligations related to realising the right to adequate food (a foretaste of which was seen most recently during the World Trade Organisation ninth ministerial conference in 2013 December which brought to the fore disagreements about governments’ own procurement of food for public programmes as distorting world trade).

The concentration of wealth in India’s cities, in its biggest cities, can be seen most clearly in this set of illustrations. These colourful circles describe the imbalance between the recorded wealth in the cities and in the districts.

The data come from the Reserve Bank of India’s ‘Quarterly Statistics on Deposits and Credit of Scheduled Commercial Banks’. In attempting to find and illustrate the distribution of bank deposits between India’s banking districts (there are 652) I ran quickly into the inequality challenge: how to make sense of the enormous disparities of wealth?

Graphics provides a way out. But a word about the distribution. At the 30th percentile level in the full list, a district’s bank deposits are around Rs 1,440 crore (14.43 billion). This rises to Rs 1,930 crore for the 40th, Rs 2,540 crore for the 50th, Rs 3,420 crore for the 60th, Rs 4,650 crore for the 70th, and Rs 7,420 crore for the 80th percentiles. From there the increases are much steeper: Rs 14,000 crore for the 90th and Rs 26,000 crore for the 95th percentile.

In the first image, the relative differences between bank deposits between the 30th and 60th percentiles are illustrated – a circle corresponds to bank deposits in crore and is labelled with the state code and district name. Here we see that the difference is between about Rs 1,400 crore and Rs 3,400 crore.

In the second image, the scale has changed with two examples each from the 60th, 80th and 90th percentiles. The differences are now between about Rs 3,400 crore, Rs 7,400 crore and Rs 14,000 crore.

The third image is where the disparity becomes immediately clear: Rs 14,000 crore of deposits are dwarfed by the tenth and ninth districts of the top ten – about Rs 79,000 crore and Rs 94,000 crore. And the last image shows the vast gap within the top ten – at this scale the districts which have less than Rs 3,400 crore deposits would be mere dots, and there are close to 400 of these districts!

This helps explain the structures of power in the cities and how one of the ways India’s wealth is recorded (no black money estimates, or property valuations, or stock or futures holdings) shows the staggering extent of inequality. Yes, the top ten banking districts – all heavily urbanised metropolises – have huge populations, but any per capita division would also have to take into account business and industry deposits and the large numbers of informal sector labour – households whose capacity to save may be only marginally better than that of households in rural districts.

How much cereals (rice, wheat, millet, sorghum) and pulses do rural Indians consume in a month? In general, not anywhere near how much they should.

The circles in this chart represent the rural population of 20 of India’s largest states by population. The National Sample Survey Office (NSSO) divides the rural (and also the urban) population of each state into tenths (they call them ‘deciles’), and the NSS surveys on consumption expenditure tell us how much each decile in each state spends, for example between Rs 800 and Rs 950 a month.

I made this chart using data from the NSS report, ‘Level and Pattern of Consumer Expenditure’ (the 66th Round, which surveyed the population between 2009 July and 2010 June). With 20 states and ten categories each, I had 200 readings to plot, examining the consumption in quantities for cereals and pulses.

Depending on the population of the state, some of those circles represent 3-5 million people! Now here is the grim finding. Of these, 72 do not meet even 75% of the minimum cereals requirement (about 10.4 kg) a month, and 106 do not meet even 50% of the minimum pulses requirement (about 0.6 kg) a month – these are the National Institute of Nutrition recommended dietary allowances. And 43 of these deciles are severely deficient in both.

How can the state explain the existence of these huge deficits in basic nutrition (see the coloured area of the chart, which includes tens of millions) while simultaneously chasing ‘growth’ as the means to remove those deficits?

For the last week, there has been a great deal of comment and discussion about how the increase in expenditure – especially in rural India – is ‘evidence’ of increasing incomes, of widening prosperity and a general ‘lifting out of poverty’. It is misleading because neither the central government nor its supporters (there are many supporting views to be found in the media) has pointed out that an increase in expenditure will of course take place given the rise in the price of food and fuel.

Comparing what the NSS has surveyed in 2009-10 with its 2004-05 survey, in some areas of expenditure the rupee rise is 300%-400% (such as for the eggs fish and meat, fresh fruit and beverages categories) and it will be useful to extract the quantities behind these increases in expenditure (I will get around to doing this as soon as possible).

In any case, the quantities consumed for cereals and pulses have actually declined for rural and urban citizens. While the proportion of expense, out of total food expense (all-India figures for rural populations), on pulses and on milk (and milk products) has remained roughly the same – 5.6% to 5.2% and 15.3% to 15.2% – the proportion spent on cereals has dropped from 32.7% to 20.2%.

I think this an extremely significant change that can be read together with the two big increases in proportion of spending – on egg fish and meat from 6% to 9% and on beverages from 8.2% to 15%. In the NSS definition, beverages also includes purchased meals and processed food, and it is this conversion of primary cereals (including coarse cereals) and pulses to processed foods that I see as an important factor behind the biggest change in the proportions spent on food in recent years.

What do and what can rural residents spend on food and the essentials of living in India? This chart gives us an indication. It is based on new data contained in the latest revelation (my word, not theirs) from the National Sample Survey Office and is titled ‘Key Indicators of Household Consumer Expenditure in India’ (the 68th Round of sampling, for those who follow the extraordinary programme of this sterling statistical organisation).

There is data enough in the volume to inform us, clearly and starkly, that the cumulative impact of several years of food price inflation is hurting households more with every passing quarter. Consider what this new data release tells us:

* That the average rural monthly expenditure per person was lowest in the states of Odisha and Jharkhand (around Rs 1,000) and also in Chhattisgarh (Rs 1,027).
* In Bihar, Madhya Pradesh and Uttar Pradesh, the rural monthly expenditure per person was about Rs 1,125 to Rs 1,160.
* In urban India (not shown in this chart, but I will add to this posting with an expanded update) Bihar had the lowest monthly expenditure per person (called monthly per capita expenditure by the NSSO and abbreviated to MPCE) of Rs 1,507.
* In Chhattisgarh, Odisha, Jharkhand, Uttar Pradesh and Madhya Pradesh, urban MPCE was between Rs 1,865 and Rs 2,060. These six were the six major states with the lowest MPCEs for both rural and urban citizens.

But those are averages, and in this data release, the NSSO has divided its usual ten deciles even further for the lowest and highest deciles. (The decile is the surveyed population divided into tenths, with these being classified by expenditure level.) Doing so gives us a better view of the elastic expense trends in the top ten per cent of the population, the class which is so pampered by the central government. For rural India then, the 5th percentile of the MPCE distribution was estimated as Rs 616 and the 10th percentile as Rs 710 – and these are all-India averages.

About half the total rural population is thus estimated to have a MPCE below Rs 1,198. Only about 10% of the rural population reported household MPCE above Rs 2,296 and only 5% reported MPCE above Rs 2,886 (this is using what is called the ‘modified mixed reference period’ or MMRP, in which the person interviewed is asked to recall purchases made over two different lengths of time, for different sorts of goods). The bottom-line is that food accounted for about 53% of the value of the average rural Indian’s household consumption during 2011-12.

This included 11% for cereals and cereal substitutes, 8% for milk and milk products, another 8% on beverages and processed food, and 6.5% on vegetables. Among non-food item categories, fuel for cooking and lighting accounted for about 8%, clothing and footwear for 7%, medical expenses for about 6.5%, education for 3.5%, conveyance for 4%, other consumer services for 4%, and consumer durables for 4.5%.

This ought to be a ringing alarm about access to food for the country’s planners, who are otherwise obsessed with GDP growth and whether India is cosmetically dolled up enough to attract global finance capital. It hasn’t sounded even a muted gong, and even if it had, one stunning inference from this table has been ignored – that this is an indicator of food and multi-dimensional poverty and that millions of rural residents are unable to afford food and basic services.

How so? Look at the chart again. Imagine, at just above the line marking 2,000 rupees, a dotted red line at a level of around 2,070 rupees. That is the equivalent (before the recent fall in the rupee’s value against the US dollar) of USD 1.25 a day, which has (ill-advisedly) been cemented in development wisdom as a poverty line that can be applied in countries like India. Let’s accept that in order to focus on what the new NSSO data tells us.

At the Rs 2,070 level we see that for a relatively prosperous state like Haryana (a former Green Revolution state) about 50% of the rural population cannot spend, per person per month, this amount. The percentage of the rural population below and above this line is similar, more or less, for Punjab (also a former Green Revolution state) and for Kerala (which is not, but has income from economic migrants abroad).

But the entire rural populations of Bihar, Chhattisgarh, Jharkhand and Odisha cannot spend this amount, because they do not earn it. How many is that? Using the 2001-2011 population growth rates (for rural populations of states) this means 98.96 million in rural Bihar, 20.65 million in rural Chhattisgarh, 26.52 million in rural Jharkhand and 36.19 million in rural Odisha are below this line. What of other states with large rural populations?

In Assam, Madhya Pradesh, Uttar Pradesh and West Bengal, 90% of the rural population is below this line and that means 25.23 million in Assam, 49.90 million in Madhya Pradesh, 147.25 million in Uttar Pradesh, and 57.26 million in West Bengal. In Gujarat, Karnataka, Maharashtra and Rajasthan, 80% of the rural population is below this line and that means 28.52 million in Gujarat, 30.66 million in Karnataka, 50.77 million in Maharashtra and 43.55 million in Rajasthan. In Andhra Pradesh and Tamil Nadu, 70% of the rural population is below this line and that means 39.64 million in Andhra Pradesh and 26.56 million in Tamil Nadu.

Taken together those rural populations are 681.72 million (more than twice the population of the USA). They are 78% of India’s 2013 rural population, almost eight out of ten rural citizens.

This is the picture of Europe today (and of the non-European members of the OECD). “Looking at the 17 OECD countries for which data are available over a long time period, market income inequality increased by more over the last three years than what was observed in the previous 12 years,” observed the new briefing, which is sub-titled ‘Crisis squeezes income and puts pressure on inequality and poverty’.

Annual percentage changes in household market income between 2007 and 2010, by income component. Chart: OECD

The figures and data show that many of the countries recording the most dramatic increases in inequality are European countries which have been subjected to punitive austerity measures by the European Union and International Monetary Fund. The OECD report singles out Spain and Italy, where the income of “the poorest 10 percent was much lower in 2010 than in 2007”.

Five percent falls in income (per year) amongst the poorest 10 percent were also recorded in Greece, Ireland, Estonia, and Iceland. The only non-European nation with a comparable level of income decline was Mexico. The report also stated that over the same period, poor families in the United States, Italy, France, Austria and Sweden all recorded income losses in excess of the OECD average.

Indeed the ‘New Results’ briefing has showed that across OECD countries, real household disposable income stagnated. Likewise, the average income of the top 10% in 2010 was similar to that in 2007. Meanwhile, the income of the bottom 10% in 2010 was lower than that in 2007 by 2% per year. Out of the 33 countries where data are available, the top 10% has done better than the poorest 10% in 21 countries.

This is the OECD picture till 2010. Since then, recession has been the companion of inequality. With an average growth of -0.2 per cent in the first quarter (against -0.1 per cent in the EU as a whole) and hardly better prospects for the whole rest of the year (-0.7 per cent), according to Eurostat, the dreaded “double dip” has become a reality. The press attributes the result largely to the austerity policies.

Gini coefficient of household disposable income and gap between richest and poorest 10%, 2010: Chart: OECD

“Eurozone sets bleak record of longest term in recession,” reported the Financial Times. The daily noted that “this latest dismal record came after unemployment hit 12.1 per cent in the bloc, its highest level,” and that this data “is likely to add to pressure on the European Central Bank to take further action after cutting interest rates this month, and to revise down its economic forecast predicting a recovery later in the year.”

Moreover, relative income poverty – the share of people having less income than half the national median income – affects around 11% of the population on average across OECD countries. Poverty rates range between 6% of the population in Denmark and the Czech Republic to between 18% and 21% in Chile, Turkey, Mexico and Israel. Over the two decades up to 2007, relative income poverty increased in most OECD countries, particularly in countries that had low levels of income poverty in the mid-1990s.

In Sweden, Finland, Luxembourg and the Czech Republic, the income poverty rate increased by 2 percentage points or more. In Sweden, the poverty rate in 2010 (9%) was more than twice what it was in 1995 (4%). Relative poverty also increased in some countries, such as Australia, Japan, Turkey and Israel, with middle and high levels of poverty.

The OECD briefing has stated bluntly: “Households with children were hit hard during the crisis. Since 2007, child poverty increased in 16 OECD countries, with increases exceeding 2 points in Turkey, Spain, Belgium, Slovenia and Hungary.” The ‘New Results’ briefing added: “Since 2007, youth poverty increased considerably in 19 OECD countries. In Estonia, Spain and Turkey, an additional 5% of young adults fell into poverty between 2007 and 2010. In the United Kingdom and Ireland, the increase was 4%, and in the Netherlands 3%.”

Annual percentage changes in household disposable income between 2007 and 2010, by income group. Chart: OECD

Between 2007 and 2010, average relative income poverty in the OECD countries rose from 12.8 to 13.4% among children and from 12.2 to 13.8% among youth. Meanwhile, relative income poverty fell from 15.1 to 12.5% among the elderly. This pattern confirms the trends described in previous OECD studies, with youth and children replacing the elderly as the group at greater risk of income poverty across the OECD countries.

These results only tell the beginning of the story about the consequences of austerity, growing unemployment, the burden on children and youth, and burden on immigrant wage labour. The OECD data describes the evolution of income inequality and relative poverty up to 2010. But “the economic recovery has been anaemic in a number of OECD countries and some have recently moved back into recession”, said the briefing.

Worse, since 2010, many people exhausted their rights to unemployment benefits. In such a situation, the briefing has warned, “the ability of the tax-benefit system to alleviate the high (and potentially increasing) levels of inequality and poverty of income from work and capital might be challenged”. These are unusually blunt words from the OECD and their use reflects the depth and persistence of the crisis of modern, reckless, destructive capitalism in Europe.

The 27 cities shown on this map are no different from many others like them in India today, and the selection of these 27 is based solely on a single numerical milestone which I am fairly sure few of each city’s citizens (or administrations for that matter) will have marked.

On some day during the months since March 2011, the population of each of these 27 cities has crossed 150,000 – this is the criterion. March 2011 is the month to which the Census 2011 has fixed its population count, for the country, for a state, a district, a town.

When the provisional results of the Census of India 2011 were released, through the year 2011, the number of cities with populations of a million and over was 53.

The number of cities with over a million inhabitants, from 53 in 2013 to 63 in 2015. Cities with names in red type will reach a million in 2015.

That was the tally almost two years ago. Between the 2011 census and the 2001 census the growth rate of the urban population was 31.8% which, turned into a simple annual rate for those ten years, is just under 3.2% per year.

At this rate, in mid-2013, six more cities will have joined the list of those with a population of over a million.

Within the next few months, India will have 59 cities with populations of over a million.

By mid-2015 (the final year of the Millennium Development Goals, or MDGs), there will be another four cities with populations of over a million: Salem (in Tamil Nadu, estimated population of 1,036,066), Aligarh (in Uttar Pradesh, 1,025,255), Gurgaon (in Haryana, 1,016,698) and Moradabad (in Uttar Pradesh, 1,002,994).

That year, Bhopal (Madhya Pradesh), Thrissur (Kerala) and Vadodara (Gujarat) will have populations of over two million; the populations of Kanpur and Lucknow (both Uttar Pradesh) will cross three million and that of Surat (Gujarat) will cross five million. India will have 63 (ten more than in 2011) cities with populations of at least a million.

These are projections that have not taken into account the state-wise variations of rural and urban growth rates. Also not accounted for is migration, as the migration data from Census 2011 has yet to be released.

The concerns about recession and its impacts on poverty are seen commonly as a question mark over household incomes, over food security and often involve debates about social protection. An aspect that all too often gets ignored in this equation – no doubt because of its complexity – is health and in particular the health of women and children.

Changes in neonatal mortality rates between 1990 and 2009. The map illustrates the change in NMR between the years 1990 and 2009 for each of the 193 countries estimated. PLoS Medicine 8(8): e1001080

This is linked very closely to poverty, however we measure it, and the conditions that either cause poverty to persist (leading to chronic poverty) or cause households at risk to lapse into poverty every now and then (shock). The human development index methodolgy, which is from this year using multi-dimensional indices for poverty for the first time, helps us link health, poverty, income and economic growth (or its opposite).

The question is: is this new understanding, which is more in tune with the way households actually carry on with their lives and are actually affected by wider trends concerning economy, helping integrate the connections? If there is one good reason to ask this question, it is the new study on ‘Neonatal Mortality Levels for 193 Countries in 2009 with Trends since 1990: A Systematic Analysis of Progress, Projections, and Priorities’.

This has shown that every year, more than 8 million children die before their fifth birthday. Most of these deaths occur in developing countries and most are caused by preventable or treatable diseases. In 2000, world leaders set a target of reducing child mortality to one-third of its 1990 level by 2015 as Millennium Development Goal 4 (MDG4). This goal, together with seven others, is designed to help improve the social, economic, and health conditions in the world’s poorest countries. In recent years, progress towards reducing child mortality has accelerated but remains insufficient to achieve MDG4.

“In particular, progress towards reducing neonatal deaths – deaths during the first 28 days of life – has been slow and neonatal deaths now account for a greater proportion of global child deaths than in 1990. Currently, nearly 41% of all deaths among children under the age of 5 years occur during the neonatal period. The major causes of neonatal deaths are complications of preterm delivery, breathing problems during or after delivery (birth asphyxia), and infections of the blood (sepsis) and lungs (pneumonia). Simple interventions such as improved hygiene at birth and advice on breastfeeding can substantially reduce neonatal deaths.”

Neonatal mortality rates in 2009. The map illustrates the NMR in year 2009 for each of the 193 countries estimated. PLoS Medicine 8(8): e1001080

The researchers used civil registration systems, household surveys, and other sources to compile a database of deaths among neonates and children under 5 years old for 193 countries between 1990 and 2009. They estimated NMRs for 38 countries from reliable vital registration data and developed a statistical model to estimate NMRs for the remaining 155 countries (in which 92% of global live births occurred).

They found that in 2009, 3.3 million babies died during their first month of life compared to 4.6 million in 1990. More than half the neonatal deaths in 2009 occurred in five countries – India, Nigeria, Pakistan, China, and the Democratic Republic of Congo. India had the largest number of neonatal deaths throughout the study. Between 1990 and 2009, although the global NMR decreased from 33.2 to 23.9 deaths per 1,000 live births (a decrease of 28%), NMRs increased in eight countries, five of which were in Africa. Moreover, in Africa as a whole, the NMR only decreased by 17.6%, from 43.6 per 1,000 live births in 1990 to 35.9 per 1,000 live births in 2009.

To return to my question concerning the understanding of economics, income, health and poverty, does most current analysis see to integrate these elements, or is it still GDP-income driven? A new (2011 May) paper released by the Brookings Institution indicates that the GDP-income route is still favoured. The paper, ‘Two Trends in Global Poverty’, Geoffrey Gertz and Laurence Chandy, has said that while the overall prevalence of poverty is in retreat, the global poverty landscape is changing. “This transformation is captured by two distinct trends: poor people are increasingly found in middle-income countries and in fragile states. Both trends – and their intersection – present important new questions for how the international community tackles global poverty reduction.”

The two charts show the trajectory of 20 developing countries along three dimensions: number of poor people, degree of fragility and real income per capita. These 20 countries collectively account for 90 percent of the world’s poor in 2005, and thus largely define the evolving state of global poverty. Graphic: Brookings Institution

“The increased prevalence of poverty in middle-income countries is in many ways a trend of success. Over the past decade, the number of countries classified as low-income has fallen by two fifths, from 66 to 40, while the number of middle-income countries has ballooned to over 100. This means 26 poor countries have grown sufficiently rich to surpass the middle-income threshold. Among those countries that have recently made the leap into middle-income status are a group of countries – India, Nigeria and Pakistan – containing large populations of poor people. It is their “graduation” which has brought about the apparent shift in poverty from the low-income to middle-income country category.”

This categorisation of middle, low and high income was to an extent useful in the 1970s, when the idea of a human development index was being discussed, but we’ve come a long way since. We know that even in smaller countries (rather, countries with populations that are relatively small compared to those whic bear the sort of burdens studied in the PLoS Medicine research) there is a great deal of income disparity. ‘Income’ itself is a condition with a bewildering number of inputs – social science is quite inadequate to the task of being able to recognise all of these, let alone quantify them and rationalise them across countries and regions – which is exactly what studies like this try to do unfortunately.

“In 2005, when more than half the world’s poor lived in such countries, it made some sense to think about fighting poverty in terms of a single developing country paradigm, based on what worked in countries such as Ghana, Tanzania, Mozambique or Vietnam,” Gertz and Chandy have said. “This logic was evident in two of the major events of that year which continue to shape today’s development agenda: the G8 meeting at Gleneagles and the High Level Forum on Aid Effectiveness in Paris. It was also apparent in Jeffrey Sachs’ influential 2005 best-seller, ‘The End of Poverty’. The legacy of these ideas is scattered throughout the work of the international development community in the design of traditional aid instruments and the standard methods of country engagement.”

The authors of the Brookings paper have said that this approach remains relevant for some countries, but with 90 percent of the world’s poor living in different settings today, its broader application can no longer be justified. Yet they have found that such an admission poses a dilemma. The dilemma exists because one of the reasons the stable low-income paradigm has persisted is because it characterizes an environment in which the international development community feels most comfortable and has the most experience. “The role of external actors in supporting poverty reduction in stable low-income countries is well understood and the standard tools of external assistance – financial and technical assistance – are well suited to them.”

Maplecroft's 2011 food security risk index

What does this mean? Does it give us a hitherto obscured insight into the inner world of aid agencies and international development departments and how they see ‘poor’ countries’ populations? Does it mean that we are burdened with three decades worth of simplistic labelling of populations at risk simply because labelling them any other way makes it difficult to help them? That’s what it looks like to me and I’d like to thank Gertz and Chandy for revealing this. But it’s way past high time this sort of categorisation was ditched, once and for all. It would do us and the battalions of development professionals a huge amount of good to simply be able to say, every so often, “we don’t know enough”.

It is worth being honest about the state of our knowledge concerning the lives of the the majority of households in ‘developing’ countries. Some of the reasons why such honesty will help in the long term are contained in a thoughtful new publication from the World Bank (whose army of development professionals will benefit from its reading). This collection is entitled ‘No Small Matter: The Impact of Poverty, Shocks, and Human Capital Investments in Early Childhood Development’ (The World Bank, 2011) and it has said that, as the 2008 global financial crisis has again demonstrated, economic crises are an unfortunate recurring event in the world and can have severe consequences for household livelihoods.

Progress in key health indicators, UN Human Development Report 2010

‘No Small Matter’ defines economic crises as sharp, negative fluctuations in aggregate income, these being especially common in developing countries, and the frequency with which they occur has been increasing in recent history. We know that declines in household and community resources are not the only risks that arise from an economic crisis because of its aggregate nature. We also know – from fieldwork and by hearing those whom we would wish to help – that at the same time as households cope with the possibility of reduced income from aggregate economic contractions, vital public services may also experience a decline in quality or availability, which in turn may have an additional impact on skill development among children. This is happening now, in more countries than ever before. The economic crisis that hit Latin America in 1982 led to a decrease in public health spending and had a disproportionate effect on the poorest groups. In 2011, the decrease in public health spending exists in many more countries.

A chapter in ‘No Small Matter’, ‘The Influence of Economic Crisis on Early Childhood Development: A Review of Pathways and Measured Impact’, by Jed Friedman and Jennifer Sturdy, is particularly useful.

This has said that “conservative estimates suggest that over 200 million children under five years of age living in developing countries fail to reach their cognitive development potential because of a range of factors, including poverty, poor health and nutrition, and lack of stimulation in home environments”. It is possible, the chapter’s authors have said, that this burden increases during times of crisis as poverty increases and food security is threatened. However, to investigate this claim more carefully it is necessary to understand the pathways through which poverty influences skill acquisition in children.

“The most severe condition affecting ECD (Early Childhood Development) is infant and early child mortality. Sharp economic downturns were associated with increases in infant mortality in Mexico, Peru and India. The mortality of children born to rural and less educated women is more sensitive to economic shocks, which suggests that the poor are disproportionately affected during most economic crises, and perhaps the poor face important credit constraints that bind in tragic ways during large contractions.

Weak relationship between economic growth and changes in health and education, UN Human Development Report 2010

The mortality of girls is also significantly more sensitive to aggregate economic shocks than that of boys. This gender differential exists even in regions such as Sub-Saharan Africa that are not particularly known for son preference and indicates a behavioral dimension where households conserve resources to better protect young sons at the expense of daughters.”

Children of poor households are more likely to die, UN Human Development Report 2010

The study found that of the 40 countries with the highest NMRs in 2009, only six are from outside the African continent (Afghanistan, Pakistan, India, Bhutan, Myanmar, and Cambodia). Among the 15 countries with the highest NMRs (all above 39), 12 were from the African region (Democratic Republic of the Congo, Mali, Sierra Leone, Guinea-Bissau, Chad, Central African Republic, Burundi, Angola, Mauritania, Mozambique, Guinea, and Equatorial Guinea), and three were from the Eastern Mediterranean (Afghanistan, Somalia, and Pakistan). Throughout the period 1990–2009, India has been the country with largest number of neonatal deaths. In 2009, the five countries with most deaths accounted for more than half of all neonatal deaths (1.7 million deaths = 52%), and 44% of global livebirths: India (27.8% of deaths, 19.6% of global livebirths), Nigeria (7.2%, 4.5%), Pakistan (6.9%, 4.0%), China (6.4%, 13.4%), and Democratic Republic of the Congo (4.6%, 2.1%). The top five contributors to the 4.6 million neonatal deaths in 1990 were: India (29.5% of deaths, 19.8% of global livebirths), China (12.3%, 18.0%), Pakistan (5.4%, 3.4%), Bangladesh (5.0%, 2.9%), and Nigeria (4.8%, 3.3%).

As the risk of children dying before the age of five has fallen, the proportion of child deaths that occur in the neonatal period has increased. This increase is primarily a consequence of decreasing non-neonatal mortality in children under five from infectious diseases such as measles, pneumonia, diarrhea, malaria, and AIDS. Globally, 41% of under-five deaths now occur in the neonatal period. Over the 20 y between 1990 and 2009, the proportion of global neonatal deaths that occurred in Africa increased. Although Africa is now the region with the highest NMR, the proportion of under-five child deaths that are neonatal remains relatively low in Africa—the fraction increased from 26% to 29% between 1990 and 2009. This apparent anomaly reflects the fact that Africa accounts for approximately 90% of child deaths due to malaria (0.7 million under-five deaths) and HIV/AIDS (0.2 million under-five deaths), resulting in relatively higher post-neonatal child mortality than other regions.

“Resource-conserving, low-external-input techniques have a proven potential to significantly improve yields,” Olivier De Schutter, the United Nations Special Rapporteur on the Right to Food, has told the UN Human Rights Council at its Sixteenth session.

“In what may be the most systematic study of the potential of such techniques to date, Jules Pretty et al. compared the impacts of 286 recent sustainable agriculture projects in 57 poor countries covering 37 million hectares (3 per cent of the cultivated area in developing countries). They found that such interventions increased productivity on 12.6 millions farms, with an average crop increase of 79 per cent, while improving the supply of critical environmental services.”

“Disaggregated data from this research showed that average food production per household rose by 1.7 tonnes per year (up by 73 per cent) for 4.42 million small farmers growing cereals and roots on 3.6 million hectares, and that increase in food production was 17 tonnes per year (up 150 per cent) for 146,000 farmers on 542,000 hectares cultivating roots (potato, sweet potato, cassava). After UNCTAD and UNEP reanalyzed the database to produce a summary of the impacts in Africa, it was found that the average crop yield increase was even higher for these projects than the global average of 79 per cent at 116 per cent increase for all African projects and 128 per cent increase for projects in East Africa.”

Olivier De Schutter, United Nations Special Rapporteur on the Right to Food

The most recent large-scale study points to the same conclusions, De Schutter has said. Research commissioned by the Foresight Global Food and Farming Futures project of the UK Government reviewed 40 projects in 20 African countries where sustainable intensification was developed during the 2000s. The projects included crop improvements (particularly improvements through participatory plant breeding on hitherto neglected orphan crops), integrated pest management, soil conservation and agro-forestry. By early 2010, these projects had documented benefits for 10.39 million farmers and their families and improvements on approximately 12.75 million hectares. Crop yields more than doubled on average (increasing 2.13-fold) over a period of 3-10 years, resulting in an increase in aggregate food production of 5.79 million tonnes per year, equivalent to 557 kg per farming household.

The Special Rapporteur’s recommendations:
As part of their obligation to devote the maximum of their available resources to the progressive realization of the right to food, States should implement public policies supporting the adoption of agroecological practices by:
• making reference to agroecology and sustainable agriculture in national strategies for the realisation of the right to food and by including measures adopted in the agricultural sector in national adaptation plans of action (NAPAs) and in the list of nationally appropriate mitigation actions (NAMAs) adopted by countries in their efforts to mitigate climate change;• reorienting public spending in agriculture by prioritizing the provision of public goods, such as extension services, rural infrastructures and agricultural research, and by building on the complementary strengths of seeds-and-breeds and agroecological methods, allocating resources to both, and exploring the synergies, such as linking fertilizer subsidies directly to agroecological investments on the farm (“subsidy to sustainability”);
• supporting decentralized participatory research and the dissemination of knowledge about the best sustainable agricultural practices by relying on existing farmers’ organisations and networks, and including schemes designed specifically for women;
• improving the ability of producers practicing sustainable agriculture to access markets, using instruments such as public procurement, credit, farmers’ markets, and creating a supportive trade and macroeconomic framework.

The research community, including centres of the Consultative Group on International Agricultural Research and the Global Forum on Agricultural Research, should:
• increase the budget for agroecological research at the field level (design of sustainable and resilient agroecological systems), farm and community levels (impacts of various practices on incomes and livelihoods), and national and sub-national levels (impact on socio-economic development, participatory scaling-up strategies, and impacts of public policies), and develop research with the intended beneficiaries according to the principles of participation and coconstruction;
• train scientists in the design of agroecological approaches, participatory research methods, and processes of co-inquiry with farmers, and ensure that their organizational culture is supportive of agroecological innovations and participatory research;
• assess projects on the basis of a comprehensive set of performance criteria (impacts on incomes, resource efficiency, impacts on hunger and malnutrition, empowerment of beneficiaries, etc.) with indicators appropriately disaggregated by population to allow monitoring improvements in the status of vulnerable populations, taking into account the requirements of the right to food, in addition to classical agronomical measures.